Affirm, Inc. is a forward-thinking fintech company known for its innovative approach to providing financial flexibility and eliminating debt traps through transparent, user-friendly services. Joining Affirm as a Business Analyst involves playing a critical role in leveraging data to drive business decisions, optimize processes, and contribute to the overall success of the company’s financial products and services.

To excel in this role, you will need a robust set of skills in data analysis, problem-solving, and communication to effectively collaborate with cross-functional teams. This guide, brought to you by Interview Query, aims to walk you through Affirm's interview process, commonly asked questions, and preparation tips to help you succeed in your journey with Affirm.

Submitting Your Application

The first step is to submit a compelling application that showcases your technical skills and enthusiasm for joining Affirm, Inc., as a Business Analyst. Whether you were contacted by an Affirm recruiter or decided to apply proactively, ensure that your CV and cover letter are tailored to the specific role.

Tailoring your application may include emphasizing particular keywords related to the job description and highlighting relevant skills and experiences that illustrate your fit for the role.

Recruiter/Hiring Manager Call Screening

If your application successfully catches the eye of Affirm’s hiring team, a recruiter from the Talent Acquisition Team will reach out to verify key details such as your experience and technical skill level. During this initial screening, you may also be asked a mix of behavioral and standard HR questions.

In some instances, the Business Analyst hiring manager might participate in this call to answer questions about the role and provide more context about the company. These calls usually last around 30 minutes.

Technical & Behavioral Phone Screen

After clearing the recruiter screening, you'll move on to a phone screen with the hiring manager. This interview typically takes about an hour and focuses on your previous experience, knowledge about products, and some behavioral questions. The hiring manager may discuss specific details about the team and even give hints about the next stages of the interview process.

Challenge Interview

If you progress past the phone screens, you'll be invited to the challenge interview. This interview includes both an execution task and a strategy design discussion. For example, you may be asked to define North Star metrics for a company like Airbnb, or strategize how Amazon could enter a new market. The challenge interview usually involves a mix of product managers and takes about 2 hours to complete.

Onsite Interview Rounds

If you successfully navigate through the challenge interview, you’ll be invited to an onsite interview. The onsite interview generally includes multiple sessions with different team members, such as engineering managers and PMs. These interviews will dig deeper into your technical and behavioral competencies and usually last around 2.5 hours in total.

HR will set up a call beforehand to walk you through what to expect and the types of questions you might encounter. Feedback is typically provided within a few business days for each stage, ensuring a well-organized and transparent process.

Quick Tips For Affirm Business Analyst Interviews

Here are a few tips for acing your Affirm interview:

• Prepare Thoroughly: Affirm's interview process includes several stages, each with its unique requirements. Focus on brushing up on basic technical skills, case studies, and behavioral questions to be well-prepared.
• Understand Affirm’s Products: Familiarize yourself with Affirm’s products and think about how you might propose improvements or measure their success. This understanding will be crucial during the product and design problem-solving segments of your interviews.
• Communicate Clearly: Transparency and clarity in your answers can make a significant difference. During the high-stress interview scenarios, keep your responses structured and to the point, particularly during the challenge interviews and onsite rounds.

To further refine your interview skills and gain insights from other similar interview experiences, consider exploring more interviews on Interview Query. Interview Query provides a wealth of resources for practicing and preparing for specific company roles.

Typically, interviews at Affirm vary by role and team, but commonly Business Analyst interviews follow a fairly standardized process across these question topics.

• What are the Z and t-tests, and when should you use each? Explain the purpose and differences between Z and t-tests. Describe scenarios where one test is preferred over the other.

• How would you reformat student test score data for better analysis? Given two datasets of student test scores, identify drawbacks in their current format. Suggest formatting changes and discuss common issues in "messy" datasets.

• What metrics would you use to evaluate the value of marketing channels? Given data on marketing channels and costs for a B2B analytics dashboard company, identify key metrics to determine the value of each marketing channel.

• How would you determine the next partner card using customer spending data? With access to customer spending data, outline the process to identify the best partner for a new credit card offering.

• How would you investigate if a redesigned email campaign led to increased conversion rates? Analyze the impact of a redesigned email campaign on conversion rates, considering other potential factors that could influence the observed increase.

• Write a function search_list to check if a target value is in a linked list. Write a function, search_list, that returns a boolean indicating if the target value is in the linked_list or not. You receive the head of the linked list, which is a dictionary with keys value and next. If the linked list is empty, you'll receive None.

• Write a query to find users who placed less than 3 orders or ordered less than $500 worth of product. Write a query to identify the names of users who placed less than 3 orders or ordered less than $500 worth of product. Use the transactions, users, and products tables.

• Create a function digit_accumulator to sum every digit in a string representing a floating-point number. You are given a string that represents some floating-point number. Write a function, digit_accumulator, that returns the sum of every digit in the string.

• Develop a function to parse the most frequent words used in poems. You're hired by a literary newspaper to parse the most frequent words used in poems. Poems are given as a list of strings called sentences. Return a dictionary of the frequency that words are used in the poem, processed as lowercase.

• Write a function rectangle_overlap to determine if two rectangles overlap. You are given two rectangles a and b each defined by four ordered pairs denoting their corners on the x, y plane. Write a function rectangle_overlap to determine whether or not they overlap. Return True if so, and False otherwise.

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates multiple decision trees and combines their results. Discuss the advantages of using random forest over logistic regression, such as handling non-linear data and reducing overfitting.

• When would you use a bagging algorithm versus a boosting algorithm? Compare the use cases for bagging and boosting algorithms. Provide examples of tradeoffs, such as bagging reducing variance and boosting improving accuracy but being more prone to overfitting.

• How would you evaluate and compare two credit risk models for personal loans?

• Identify the type of model developed by the co-worker for loan approval.
• Describe how to measure the difference between two credit risk models over a timeframe, considering monthly installments.

• List metrics to track the success of the new model, such as accuracy, precision, recall, and AUC-ROC.

• What’s the difference between Lasso and Ridge Regression? Explain the key differences between Lasso and Ridge Regression, focusing on their regularization techniques and how they handle feature selection and multicollinearity.

• What are the key differences between classification models and regression models? Describe the main differences between classification and regression models, including their objectives, output types, and common use cases.

• How would you design a function to detect anomalies in univariate and bivariate datasets? If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? Assume you have data on student test scores in two layouts. Identify the drawbacks of these formats, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• What is the expected churn rate in March for customers who bought a subscription since January 1st? You noticed that 10% of customers who bought subscriptions in January 2020 canceled before February 1st. Assuming uniform new customer acquisition and a 20% month-over-month decrease in churn, calculate the expected churn rate in March for all customers since January 1st.

• How would you explain a p-value to a non-technical person? Describe what a p-value is in simple terms for someone who is not familiar with technical or statistical concepts.

• What are Z and t-tests, and when should you use each? Explain what Z and t-tests are, their uses, differences, and when to use one over the other.

If you're preparing for a business analyst position at Affirm, Inc., understanding their multi-stage interview process is crucial. From engaging recruiter calls to detailed system design and coding challenges, the journey is both demanding and comprehensive. It's clear that Affirm values both technical prowess and cultural fit, making extensive preparation essential. Whether you're tackling leetcode-style tasks or addressing behavioral queries, every interaction can be pivotal. Experiences have varied, with some candidates praising the thoroughness and feedback of their interviewers, while others have faced challenges and inconsistencies.

For an in-depth understanding and strategic preparation, check out our main Affirm Interview Guide on Interview Query. We've compiled numerous interview questions and tailored guides for different roles, such as software engineer and data analyst, to help you navigate Affirm’s interview landscape.

At Interview Query, we provide you with all the tools you need to build confidence and ace your Affirm interviews. Visit our company interview guides for more preparation tips, and don't hesitate to reach out if you have any questions.

Good luck with your interview!